Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add personamanagmentlayer/pcl --skill edge-computing-expertgit clone --depth 1 https://github.com/personamanagmentlayer/pclWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/personamanagmentlayer/pcl/edge-computing-expert)<a href="https://agentmods.dev/skills/personamanagmentlayer/pcl/edge-computing-expert"><img src="https://agentmods.dev/badge/skills/personamanagmentlayer/pcl/edge-computing-expert/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/personamanagmentlayer/pcl/edge-computing-expert"><img src="https://agentmods.dev/badge/skills/personamanagmentlayer/pcl/edge-computing-expert.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00057 | $0.01175 |
| Opus 5 | $0.00028 | $0.00588 |
| Sonnet 5 | $0.00011 | $0.00235 |
| Haiku 4.5 | $0.00006 | $0.00118 |
Grade A, and why
edge-computing-expert scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 185 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Edge Computing Expert
Design and implement production-grade edge computing solutions including CDN optimization, fog computing architectures, and distributed edge workloads.
Learning Objectives
- Master edge computing architectures and patterns
- Implement CDN optimization and caching strategies
- Build fog computing distributed systems
- Deploy edge workloads with container orchestration
- Optimize for ultra-low latency applications
Prerequisites
- Strong understanding of distributed systems
- Knowledge of networking and protocols
- Experience with containers and orchestration
- Familiarity with cloud computing concepts
Core Concepts
Edge Computing Architecture
Computing paradigm that brings data processing closer to data sources (IoT devices, users, sensors) rather than centralized cloud data centers. Reduces latency, bandwidth costs, and enables real-time processing.
Content Delivery Networks (CDN)
Geographically distributed network of proxy servers that cache and deliver content from locations closer to end users. Improves load times, reduces origin server load, and enhances availability.
Fog Computing
Decentralized computing infrastructure where data, compute, storage, and applications are distributed between the data source and the cloud. Extends cloud capabilities to the edge of the network.
Multi-Access Edge Computing (MEC)
Network architecture providing IT and cloud computing capabilities at the edge of mobile networks. Enables ultra-low latency applications by processing data near 5G base stations.
Edge Orchestration
Management and coordination of distributed edge workloads across heterogeneous edge infrastructure. Includes deployment, scaling, monitoring, and failover of edge services.
Best Practices
Edge Architecture Design
- Place edge nodes based on user density and latency requirements
- Implement multi-tier edge hierarchy (device → edge → regional → cloud)
- Design for intermittent connectivity and offline operation
- Use event-driven architectures for asynchronous processing
- Implement circuit breakers and fallback mechanisms
- Distribute workloads based on data locality
- Plan for edge node heterogeneity
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 185 lines · 57 tokens per session scan A 20960a404512
edge-computing-expert is a skill published in the GitHub repository personamanagmentlayer/pcl (40 stars, last pushed yesterday), licensed Apache-2.0. It adds 57 tokens to every session and 1,175 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.
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